The present invention generally relates to electronic display control, and more particularly, to a frame rate conversion apparatus and method in which frames are converted.
Conventionally, in personal computers (PC) or high-definition televisions (HDTV), frame rate conversion may be performed for compatibility between programs having various broadcasting signal standards such as PAL or NTSC. Frame rate conversion may mean conversion of the number of frames that are output per second. In particular, when a frame rate is increased, interpolation of a new frame may be required. The interpolated frame may be referred to as an interpolation frame. To generate the interpolation frame, motion estimation (ME) may be used. ME may include searching for the most similar blocks between a previous frame and a current frame. A motion vector (MV) may indicate a magnitude of block's movement in ME.
A conventional ME method may be used to reduce temporal redundancy of video data and to generate the MV. Among various ME methods for generating the MV, a block matching algorithm (BMA) may be used. The BMA may search for movement in each block and apply a motion vector corresponding to the movement to all pixels included in the block. The BMA may require a small amount of time to be executed and can be easily implemented as hardware. In a general video, motions can be classified into rotation, translation, and zoom-in/out. In this regard, it may be assumed that a motion between frames having a very small interval therebetween is very little. Therefore, the BMA may be performed on the assumption that there is only translation in a video and motions of all pixels in the same block are the same. Thus, the BMA may search for a block that is most similar to a current block of a current frame in a search range of a previous frame and determine a displacement between the two blocks as an MV. This process may be called a full search. Each block may be composed of 16×16 pixels and may be called as a macroblock (MB).
Since the full search may perform comparison with all pixels included in the search range, it can find an MV having the smallest matching error. However, the full search may require significant computation resources. In other words, the conventional BMA may result in unnecessary computation and power consumption because it may perform ME even for a portion having no motion. Moreover, the conventional BMA may perform a wrong ME by not distinguishing between a static object and a moving object. In this regard, degradation in display quality may result when the wrong ME is applied to an interpolated image.